Faster exact solution of sparse MaxCut and QUBO problems
D Rehfeldt, T Koch, Y Shinano - Mathematical Programming Computation, 2023 - Springer
The maximum-cut problem is one of the fundamental problems in combinatorial
optimization. With the advent of quantum computers, both the maximum-cut and the …
optimization. With the advent of quantum computers, both the maximum-cut and the …
Adaptive piecewise linear relaxations for enclosure computations for nonconvex multiobjective mixed-integer quadratically constrained programs
M Link, S Volkwein - Journal of Global Optimization, 2023 - Springer
In this paper, a new method for computing an enclosure of the nondominated set of
multiobjective mixed-integer quadratically constrained programs without any convexity …
multiobjective mixed-integer quadratically constrained programs without any convexity …
Progressively strengthening and tuning MIP solvers for reoptimization
KK Patel - Mathematical Programming Computation, 2024 - Springer
This paper explores reoptimization techniques for solving sequences of similar mixed
integer programs (MIPs) more effectively. Traditionally, these MIPs are solved …
integer programs (MIPs) more effectively. Traditionally, these MIPs are solved …
Rethinking and Benchmarking Predict-then-Optimize Paradigm for Combinatorial Optimization Problems
Numerous web applications rely on solving combinatorial optimization problems, such as
energy cost-aware scheduling, budget allocation on web advertising, and graph matching …
energy cost-aware scheduling, budget allocation on web advertising, and graph matching …
Online learning for scheduling MIP heuristics
Abstract Mixed Integer Programming (MIP) is NP-hard, and yet modern solvers often solve
large real-world problems within minutes. This success can partially be attributed to …
large real-world problems within minutes. This success can partially be attributed to …
GBOML: a structure-exploiting optimization modelling language in Python
Mixed-Integer Linear Programs (MILPs) have many practical applications. Most modelling
tools for MILPs fall in two broad categories. Indeed, tools such as algebraic modelling …
tools for MILPs fall in two broad categories. Indeed, tools such as algebraic modelling …
A note on integrated disassembly line balancing and routing problem
J Feng, A Che - International Journal of Production Research, 2023 - Taylor & Francis
This note comments on the study of [Diri Kenger, Zülal, Çağrı Koç, and Eren Özceylan.
2020.“Integrated Disassembly Line Balancing and Routing Problem.” International Journal …
2020.“Integrated Disassembly Line Balancing and Routing Problem.” International Journal …
On the implementation and strengthening of intersection cuts for QCQPs
The generation of strong linear inequalities for QCQPs has been recently tackled by a
number of authors using the intersection cut paradigm—a highly studied tool in integer …
number of authors using the intersection cut paradigm—a highly studied tool in integer …
[PDF][PDF] Goose: A Meta-Solver for Deep Neural Network Verification.
The verification of deep neural networks is a recent algorithmic challenge that has attracted
significant interest, resulting in a wide array of complete and incomplete solvers that draw on …
significant interest, resulting in a wide array of complete and incomplete solvers that draw on …
Vehicle routing with heterogeneous time windows
We consider a novel variant of the heterogeneous vehicle routing problem (VRP) in which
each customer has different availability time windows for every vehicle. In particular, this …
each customer has different availability time windows for every vehicle. In particular, this …